DSA In Python + Top 100 Leetcode Problems for MAANG from Udemy

The "DSA In Python + Top 100 Leetcode Problems for MAANG" course is a comprehensive training program designed to help you excel in coding interviews by focusing on the top 100 Leetcode problems.

Leetcode is a well-known platform that offers a vast collection of coding challenges frequently used by tech companies during their hiring process.

In this course, we will tackle the most frequently encountered problems in coding interviews.

Each problem will be thoroughly analyzed, providing you with valuable insights into the underlying concepts and problem-solving techniques.

You will learn how to approach problems systematically, break them down into smaller manageable tasks, and devise efficient algorithms to solve them.

A key aspect of this course is the live implementation of code.

Each problem will be demonstrated in real-time, allowing you to witness the coding process firsthand.

This practical approach will help solidify your understanding and improve your coding skills.

You will gain insights into efficient coding practices, optimization techniques, and common pitfalls to avoid.

We will go over each of the problems in extreme detail, going through the thought process, and live implementation for the code.

To support your learning journey, the course will provide code sample files accompanying the video lectures.

These resources will serve as valuable references and guides, assisting you in implementing the solutions effectively.

What's inside

Learning objectives

Learn data structures & algorithms in python from scratch
Top leetcode interview questions (previously asked)
Comprehensive preparation for python coding interviews

Leetcode practice problems on graphs, trees, backtracking in python
Visualized implementation of key faang/maang interview algorithms

Learn data structures & algorithms in python from scratch
Top leetcode interview questions (previously asked)
Comprehensive preparation for python coding interviews
Leetcode practice problems on graphs, trees, backtracking in python
Visualized implementation of key faang/maang interview algorithms

Syllabus

You will be able to understand the importance of Leetcode and understand how to learn through this course and be able to clear coding interviews

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Offers comprehensive preparation for Python coding interviews, which is essential for landing jobs at top tech companies

Provides visualized implementation of key FAANG/MAANG interview algorithms, which can greatly enhance understanding and retention

Covers time and space complexity analysis, which is a fundamental skill for algorithm design and optimization in software engineering

Includes a focus on Leetcode problems, which are frequently used by tech companies during their hiring process to assess candidates

Teaches sorting algorithms, such as bubble sort, selection sort, insertion sort, merge sort, quick sort, and counting sort

Requires familiarity with Python, so learners without prior experience may need to acquire basic Python skills beforehand

Reviews summary

Dsa & leetcode for interview prep

According to learners, this course offers a strong foundation in Data Structures and Algorithms in Python, particularly focusing on solving Top 100 Leetcode problems relevant to MAANG interviews. Many appreciate the detailed explanations and live coding demonstrations which help solidify understanding. Students highlight that the course is highly practical and directly applicable to interview preparation. However, some notes indicate that certain sections might benefit from more in-depth coverage or assuming a basic familiarity with Python before starting. Overall, it is considered a valuable resource for those serious about passing coding interviews.

Requires some prior knowledge of Python.

"While DSA is covered, a basic understanding of Python syntax and common structures is helpful before starting."

"It helps if you have some Python experience, as the course focuses more on the DSA/algorithm part."

"Not for absolute Python beginners, but great if you know the basics."

Live coding helps solidify understanding.

"Watching the code being written live for each problem was incredibly beneficial."

"The live implementation sessions really helped me grasp how to translate logic into code."

"The practical coding demonstrations are a strong point of this course."

"Seeing the code built line by line reinforces the concepts effectively."

Explanations are detailed and easy to follow.

"The instructor explains each problem and its solution logic very clearly."

"I appreciate the step-by-step breakdown of complex concepts."

"The way the algorithms are explained makes them easy to understand and implement."

"The thought process behind solving problems is articulated well."

Highly effective for coding interview readiness.

"This course is a fantastic resource for anyone preparing for coding interviews, especially at the FAANG/MAANG level."

"It directly addresses the skills needed to succeed in technical interviews."

"I feel much more confident approaching Leetcode problems after taking this course."

"Provided the necessary tools and practice for interview success."

Addresses key Leetcode problems for interviews.

"The course content covers a wide range of problems commonly asked in coding interviews, which is very helpful."

"Focusing on the top 100 Leetcode problems is exactly what I needed for interview preparation."

"I found the selection of problems to be spot-on for preparing for MAANG interviews."

"The problems selected are highly relevant to real-world interview scenarios."

"This course tackles the right problems needed for tech company interviews."

Some topics might need further study.

"While the course covers the problems well, some underlying theoretical DSA concepts could use deeper dives."

"Could benefit from additional explanations on certain advanced data structures or algorithms."

"Might need supplementary material for a complete theoretical understanding."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in DSA In Python + Top 100 Leetcode Problems for MAANG with these activities:

Review Time and Space Complexity

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Solidify your understanding of time and space complexity to better analyze and optimize algorithms covered in the course.

Browse courses on Time Complexity

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Review the definitions of Big O, Big Omega, and Big Theta notations.
Practice calculating time and space complexity for simple algorithms.
Work through examples of common data structure operations and their complexities.

Review: 'Grokking Algorithms'

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Enhance your understanding of algorithms with a visually rich and beginner-friendly guide.

View Grokking Algorithms, Second Edition on Amazon

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Read selected chapters relevant to the course syllabus.
Work through the examples and exercises in the book.
Compare the book's explanations with the course lectures.

Implement Sorting Algorithms from Scratch

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Reinforce your understanding of sorting algorithms by implementing them without relying on built-in functions.

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Choose a sorting algorithm (e.g., bubble sort, insertion sort, merge sort).
Implement the algorithm in Python, focusing on correctness and efficiency.
Test your implementation with various input arrays, including edge cases.
Compare your implementation's performance with Python's built-in sort function.

Four other activities

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Show all seven activities

Create a Video Explaining a DSA Concept

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Solidify your understanding of a specific DSA concept by creating a video explaining it to others.

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Choose a DSA concept (e.g., binary search, dynamic programming).
Prepare a script and visuals to explain the concept clearly.
Record and edit the video, ensuring good audio and video quality.
Share the video with peers and solicit feedback.

Solve LeetCode Problems on Linked Lists

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Improve your linked list manipulation skills by solving a set of LeetCode problems focused on linked lists.

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Select 5-10 linked list problems from LeetCode (easy to medium difficulty).
Solve each problem, focusing on clean and efficient code.
Analyze the time and space complexity of your solutions.
Compare your solutions with the official LeetCode solutions.

Build a Custom Hash Table

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Deepen your understanding of hash tables by building one from scratch, including collision resolution strategies.

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Design the hash table structure, including the underlying array and hash function.
Implement insertion, deletion, and search operations.
Implement a collision resolution strategy (e.g., separate chaining, open addressing).
Test your hash table with various data sets and collision scenarios.

Review: 'Cracking the Coding Interview'

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Prepare for coding interviews with a comprehensive guide covering DSA and problem-solving strategies.

View Cracking the Coding Interview on Amazon

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Read the chapters on data structures and algorithms covered in the course.
Solve the practice problems at the end of each chapter.
Review the interview tips and strategies provided in the book.

Career center

Learners who complete DSA In Python + Top 100 Leetcode Problems for MAANG will develop knowledge and skills that may be useful to these careers:

Algorithm Developer

An algorithm developer creates and implements algorithms to solve complex problems. This course is directly aligned with the core skills needed for an algorithm developer by focusing on algorithmic problem-solving techniques and data structures. Through detailed analysis and live code implementation, this course will help those seeking to become algorithm developers thoroughly understand how to build efficient algorithms. This course's focus on practical problem-solving using Leetcode examples is directly applicable to the work this role performs and will assist in preparing for rigorous technical interviews. The specific instruction on time and space complexity will give algorithm developers the tools to build efficient solutions. Those that wish to become algorithm developers may find this course particularly beneficial.

See salaries and explore the career path for Algorithm Developer

Software Engineer

A software engineer designs, develops, and tests software applications. This course helps build a foundation in coding interview preparation, which is an important component of landing a job as a software engineer. Through analyzing, problem solving, and implementing algorithms in this course, learners will be better suited to tackle the challenges faced when coding and designing software. This course specifically addresses common data structures and algorithm challenges that are a key part of the day-to-day work of a software engineer, including using arrays, linked lists, and hashmaps. The live implementation of code in this course provides practical skills necessary to succeed as a software engineer. This course may be particularly useful for those early in their careers.

See salaries and explore the career path for Software Engineer

Backend Engineer

A backend engineer focuses on the server-side logic of applications. This course will help build a foundation in data structures and algorithms, which are essential for backend engineers. The course emphasizes real-time code implementation, which is important in the day-to-day practice of backend engineering. By studying this course, backend engineers will learn how to work with arrays, linked lists, and hash tables, among other data structures. The course also teaches how to approach problems systematically and devise efficient algorithms, core skills for a backend engineer.

See salaries and explore the career path for Backend Engineer

Full-Stack Developer

A full stack developer works on both the front-end and back-end of applications. This course helps those who wish to become full stack developers by providing live coding implementations which will be useful when designing the back-end of applications. This course provides a strong understanding of data structures and algorithms, which form the basis of back-end functionality. The course's content on time and space complexity, sorting, and array manipulation will help a full stack developer write efficient and reliable code. The practical approach of this course is suited to the day-to-day work of a full stack developer.

See salaries and explore the career path for Full-Stack Developer

Data Engineer

A data engineer builds and maintains data pipelines and infrastructure. This course helps data engineers by providing a practical understanding of data structures and algorithms that are used in all parts of the data pipeline. Through this course, data engineers can improve their understanding of efficient data handling, which is a core component of their work. This course focuses on practical implementation to help data engineers design robust systems. Those that wish to become data engineers may find that this course provides the core computer science skills they need to succeed in the field.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

A machine learning engineer develops and deploys machine learning models. The detailed analysis of data structures and algorithms found in this course can be useful in optimizing the performance of machine learning models. By understanding how to implement real-time live code and developing algorithm design, a machine learning engineer may use this course to develop skills in problem solving, which is often an essential component of model design and deployment. The course also covers advanced topics such as sorting, linked lists, and hash tables, all of which can be helpful in handling and interpreting data. Those that wish to become machine learning engineers may find this course useful.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A data scientist analyzes data to extract meaningful insights. The coding skills needed for a data scientist are developed in this course, which provides a grounding in data structures and algorithms. The core competencies of a data scientist are enhanced by understanding how to approach problems systematically, break them down, and perform live implementations of code. This course also explores specific data structures as well as the performance of different algorithms to ensure that code is optimized for speed and efficiency. This course may be beneficial for data scientists, particularly those performing coding or programming as part of their work.

See salaries and explore the career path for Data Scientist

Game Developer

A game developer creates and tests video games. The core algorithm and data structures that are the focus of this course align with the core skills necessary for game development. This course may assist a game developer by focusing on problem solving, live code implementation, and creating efficient algorithms that may be used in game design. The specific data structures taught in this course are important for a game developer who needs to manage game data as well as the game engine itself. Game developers may find this course particularly helpful in enhancing their foundational computer science skills.

See salaries and explore the career path for Game Developer

Systems Analyst

A systems analyst researches and recommends solutions to improve an organization's computer systems. This course can help those who want to become systems analysts by providing the fundamentals of data structures and algorithms. This course may be useful to system analysts, who often need to identify inefficiencies in existing systems and recommend improvements. A systems analyst may use this course to help them tackle problems systematically, decompose them into smaller parts, and devise efficient solutions. This course also helps build the foundation of knowledge of algorithm design needed to be a systems analyst.

See salaries and explore the career path for Systems Analyst

Solutions Architect

A solutions architect designs and oversees the implementation of technology solutions. This course, which provides training in data structures and algorithms, can be beneficial for those seeking to become solutions architects. This course provides instruction on how to implement live code, which is a core skill for solutions design. The problem solving skills taught in this course are also critical when creating technology solutions that meet the needs of an organization. Those that wish to become solutions architects may find this course helpful in improving their fundamental skills in algorithm design.

See salaries and explore the career path for Solutions Architect

Frontend Engineer

A frontend engineer focuses on the user interface of applications. While this course focuses less directly on frontend skills, the core of problem solving and algorithm design may be useful to a frontend engineer. This course teaches learners how to break down problems into smaller parts, a skill that may be useful for a frontend engineer when creating complex interface designs and components. By providing thorough analysis and live coding implementation, this course may help give frontend engineers a more complete understanding of the fundamentals of computer science. Those that wish to become frontend engineers may find this course useful.

See salaries and explore the career path for Frontend Engineer

Technical Lead

A technical lead guides and mentors a team of engineers. While this course may not directly align with the management duties of a technical lead, the detailed instruction in algorithm design may build a foundation that is useful in daily practice. Technical leads may also use this course to refresh their knowledge, or to help others on their team. By giving detailed instruction on time and space complexity, the course may be useful to a technical lead who is tasked with designing or implementing complex systems. Technical leads may find this course helpful to refresh fundamental computer science knowledge.

See salaries and explore the career path for Technical Lead

Mobile Application Developer

A mobile application developer creates applications for mobile devices. While this course does not directly cover mobile development, the foundational computer science skills may be useful to a mobile application developer. Through this course, learners will improve their core algorithm and data structure knowledge, which are essential to building efficient mobile applications. The course's focus on practical application and live coding may be of particular benefit to mobile application developer interested in developing and maintaining systems. Mobile application developers may find this course useful to enhance their foundational skills.

See salaries and explore the career path for Mobile Application Developer

Robotics Engineer

A robotics engineer designs, builds, and maintains robots and robotic systems. This course, which provides training in data structures and algorithms, is useful for those who wish to work with the complexities of robotic systems. The systematic approach to problem-solving taught in this course is useful for designing control systems and algorithms that will be used in robotics. Those that wish to become robotics engineers may learn from this course how to approach problems systematically, break them down into smaller parts, and program solutions. Robotics engineers may find this course particularly helpful in building their foundation in algorithms.

See salaries and explore the career path for Robotics Engineer

Quantitative Analyst

A quantitative analyst, often called a quant, uses mathematical and statistical models to solve financial problems. Although this course does not focus directly on finance, the programming and problem-solving skills are useful for a quant. The systematic problem-solving approach taught in this course may be useful for quant analysts in the development of quantitative models and algorithms. This course helps quants address complex problems by teaching them to break down problems, design efficient algorithms, and implement code live. Quants may find this course helpful in enhancing their coding abilities, which may be a useful skill in quantitative finance.

See salaries and explore the career path for Quantitative Analyst

DSA In Python + Top 100 Leetcode Problems for MAANG

What's inside

Learning objectives

Syllabus

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Reviews summary

Dsa & leetcode for interview prep

Activities

Career center

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